code: def test_batch_group_shuffle(self):
      if ok_ljspeech:
          dataloader, dataset = self._create_dataloader(2, c.r, 16)
          last_length = 0
          frames = dataset.items
          for i, data in enumerate(dataloader):
              if i == self.max_loader_iter:
                  break
              text_input = data[0]
              text_lengths = data[1]
              speaker_name = data[2]
              linear_input = data[3]
              mel_input = data[4]
              mel_lengths = data[5]
              stop_target = data[6]
              item_idx = data[7]
  
              avg_length = mel_lengths.numpy().mean()
              assert avg_length >= last_length
          dataloader.dataset.sort_items()
          is_items_reordered = False
          for idx, item in enumerate(dataloader.dataset.items):
              if item != frames[idx]:
                  is_items_reordered = True
                  break
          assert is_items_reordered
  
file_path: TTS/tests/test_loader.py
imports: import os
  import shutil
  import unittest
  import numpy
  import torch
  from tests import get_tests_input_path, get_tests_output_path
  from torch.utils.data import DataLoader
  from TTS.tts.datasets import TTSDataset
  from TTS.tts.datasets.preprocess import ljspeech
  from TTS.utils.audio import AudioProcessor
  from TTS.utils.io import load_config
label_desc: Use image node_id 4 for calling the TestTTSDataset obj's underlying member method code with example usage: obj.test_batch_group_shuffle() without return types